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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

Getting brighter: Impacts of improved day-ahead solar forecasts in high-solar, high-storage electricity systems

This paper analyzes the impacts of improved day-ahead solar forecasts on costs and dispatch in the solar-rich Southeast U.S. It uses an optimized high-solar, high-storage resource portfolio in which solar generation capacity accounts for 45 % of total installed capacity (34 %–36 % of generation) and energy storage capacity (43 GW) is equivalent to 33 % of peak demand. In a base scenario, improved day-ahead solar forecasts reduce production costs by $\$87$ million per year ($\$0.13$ per MWh load, $2023$$). This level of savings is within the range or lower than earlier studies of solar forecast improvements at lower levels of solar generation (<25 % of total generation). In this study, solar expansion was accompanied by two important sources of flexibility for managing solar forecast error: energy storage and day-ahead solar curtailment. Furthermore, the analysis finds that regional coordination complements day-ahead solar forecast improvements while natural gas commitment flexibility is a substitute for forecast improvements, as the improved solar forecast leads to sub-optimal commitment of thermal units. Day-ahead solar forecast improvements reduce reserves required to manage forecast error by 30 %. Fewer reserves to manage large, infrequent solar forecast errors could be an important benefit of improved solar forecasts.

14 SOLAR ENERGY↗

Use of Physics to Improve Solar Forecast: Part II, Machine Learning and Model Interpretability

Machine learning (ML) models have been applied to forecast solar energy; however, they often lack clarity of interpretability and underlying physics. This work addresses such challenges by developing a hierarchy of ML models that gradually introduce predictors to improve the forecast accuracy based on a physics-based framework. Three ML models (ARIMA, LSTM, and XGBoost) are examined and compared with four physics-informed persistence models reported in Part I and the simple persistence model to assess the improvement of different models. The 7-year measurements at the U.S. Department of Energy's Atmospheric Radiation Measurement's Southern Great Plains Central Facility site are used for forecasts and evaluations. The results reveal that the step-by-step introduction of predictors leads to different improvements for models at different hierarchical levels. Comparison of the ML models with persistence models shows that LSTM and XGBoost outperform all the persistence models, with LSTM having the overall best performance; however, ARIMA underperforms the four physics-informed persistence models. This study demonstrates the importance and utility of incorporating physics into ML models in improving forecast accuracy by introducing a hierarchy of physics-based predictors, distinguishing predictor contributions, and enhancing the ML interpretability. The combined use of Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) significantly improves the forecast accuracy compared to using individual irradiances alone because the pair contains more information on cloud-radiation interactions.

interpretability↗

Applying Utility's Advanced Grid Technologies to Improve Resiliency of a Critical Load

The US DOE Office of Electricity's Energy Storage Program's joint R&D work with the Cordova Electric Cooperative (CEC) has deployed several advanced grid technologies that are providing benefits today to Cordova Alaska's electricity users. Advanced grid technologies deployed through DoE co-funded R&D include a 1MW Battery Energy Storage System (BESS), and enhanced monitoring including Phasor Measurement Units (PMU's) to help better understand the operational impacts of the added BESS. This paper will highlight key accomplishments to-date in deploying and using advanced grid technologies, and then outline the next phase of work that will use these technologies to implement an operating scheme to reconfigure the utility's distribution system and utility resources including BESS to provide emergency back-up power to a critical load: the Cordova Community Medical Center (CCMC). This paper will include additional insights on the use of utility resources to support critical loads via case study examples by the National Rural Electric Cooperative Assoc. (NRECA).

BESS↗

Engineering PHL7 for Improved Poly(Ethylene Terephthalate) Depolymerization via Rational Design and Directed Evolution

Enzymatic depolymerization of poly(ethylene terephthalate) (PET) has emerged as a promising approach for polyester recycling, and, to date, many natural and engineered PET hydrolase enzymes have been reported. For industrial use, PET hydrolases must achieve high depolymerization extent and exhibit excellent thermostability. Here, we engineered a natural PET hydrolase, Polyester Hydrolase Leipzig #7 (PHL7), through rational design and directed evolution using a high-throughput screening platform. Four new enzymes were engineered with enhanced properties compared with the parent enzyme, wild-type PHL7 (PHL7-WT), and other benchmark PET hydrolases, under the tested conditions. In bioreactors, the exemplary engineered enzyme, PHL7-Jemez, exhibited improved ability to depolymerize amorphous PET film compared with PHL7-WT at 2.9% and 20% substrate loadings, with 37% and 270% higher hydrolysis, respectively, after 48 h. This study develops several state-of-the-art PET hydrolases and demonstrates a directed evolution platform to engineer high-performance enzymes, which can accelerate enzyme discovery toward improved biocatalytic recycling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improving Aerosol Radiative Forcing and Climate in E3SM: Impacts of New Cloud Microphysics and Improved Wet Removal Treatments

Abstract Numerous Earth system models exhibit excessive aerosol effective forcing at the top of the atmosphere (TOA), including the Department of Energy's Energy Exascale Earth System Model (E3SM). Here, in the context of the E3SM version 3 effort, the predicted particle property (P3) stratiform cloud microphysics scheme and an enhanced deep convection parameterization suite (ZM_plus) are implemented into E3SM. The ZM_plus includes a convective cloud microphysics scheme, a multi‐scale coherent structure parameterization for mesoscale convective systems, and a revised cloud base mass flux formulation considering impacts of the large‐scale environment. The P3 scheme improved cloud and radiation particularly over the Northern Hemisphere and the frequency of heavy precipitation over the tropics, and the ZM_plus improved clouds in the tropics. P3 decreases aerosol effective forcing by 0.15 W m −2 , while the ZM_plus increases it by 0.27 W m −2 , resulting from excessive direct (0.31 W m −2 ) and indirect forcing (−1.79 W m −2 ). The excessive aerosol forcings are due to aerosol overestimation associated with insufficient aerosol wet removal. By improving the physical treatments in the aerosol wet removal, we effectively mitigate anthropogenic aerosol overestimation and thus attenuate direct (0.09 W m −2 ) and indirect aerosol forcing (−1.52 W m −2 ). Adjustment to primary organic matter hygroscopicity reduces direct and indirect forcing to more reasonable values: −0.13 W m −2 and −1.31 W m −2 , respectively. On climatology, improved aerosol treatments mitigate overestimation of aerosol optical depth.

54 ENVIRONMENTAL SCIENCES↗

Performance and characterization of the SPT-3G digital frequency-domain multiplexed readout system using an improved noise and crosstalk model

The third-generation South Pole Telescope camera (SPT-3G) improves upon its predecessor (SPTpol) by an order of magnitude increase in detectors on the focal plane. The technology used to read out and control these detectors, digital frequency-domain multiplexing (DfMUX), is conceptually the same as used for SPTpol, but extended to accommodate more detectors. A nearly 5× expansion in the readout operating bandwidth has enabled the use of this large focal plane, and SPT-3G performance meets the forecasting targets relevant to its science objectives. However, the electrical dynamics of the higher-bandwidth readout differ from predictions based on models of the SPTpol system due to the higher frequencies used and parasitic impedances associated with new cryogenic electronic architecture. To address this, we present an updated derivation for electrical crosstalk in higher-bandwidth DfMUX systems and identify two previously uncharacterized contributions to readout noise, which become dominant at high bias frequency. The updated crosstalk and noise models successfully describe the measured crosstalk and readout noise performance of SPT-3G. These results also suggest specific changes to warm electronics component values, wire-harness properties, and SQUID parameters, to improve the readout system for future experiments using DfMUX, such as the LiteBIRD space telescope.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Wind ramp events validation in NWP forecast models during the second Wind Forecast Improvement Project (WFIP2) using the Ramp Tool and Metric (RT&M)

The second Wind Forecast Improvement Project (WFIP2) is a multi-agency field campaign held in the Columbia Gorge area (October 2015 - March 2017). The main goal of the project is to understand and improve the forecast skill of numerical weather prediction (NWP) models in complex terrain, particularly beneficial for the wind energy industry. This region is well-known for its excellent wind resource. One of the biggest challenges for wind power production is the accurate forecasting of wind ramp events (large changes of generated power over short periods of time). Poor forecasting of the ramps requires large and sudden adjustments in conventional power generation, ultimately increasing the costs of power. A Ramp Tool and Metric (RT&M) was developed during the first WFIP experiment, held in the U.S. Great Plains (September 2011 - August 2012). The RT&M was designed to explicitly measure the skill of NWP models at forecasting wind ramp events. Here we apply the RT&M to 80-m (turbine hub-height) wind speeds measured by 19 sodars and 3 lidars, and to forecasts from the High Resolution Rapid Refresh (HRRR), 3-km, and from the High Resolution Rapid Refresh Nest (HRRRNEST), 750-m horizontal grid spacing, models. The diurnal and seasonal distribution of ramp events are analyzed, finding a noticeable diurnal variability for spring and summer but less for fall and especially winter. Also, winter has fewer ramps compared to the other seasons. The model skill at forecasting ramp events, including the impact of the modification to the model physical parameterizations, was finally investigated.

Djalalova, Irina V.↗

NGEE Arctic Integrated Modeling (IM2): Improved subgrid hillslope hydrologic connectivity

This data product represents the integration of new code capability for arctic tundra hillslope hydrologic processes into the Energy Exascale Earth System Model (E3SM), through the E3SM Land Model (ELM) component. This code integration is the result of collaborative effort between the NGEE Arctic project and the E3SM project. The current ELM represents water movement primarily through vertical processes, such as precipitation, canopy interception, evaporation, infiltration, and soil water movement. Lateral water movement—such as surface runoff, subsurface flow, and river transport—plays a significant role in the hydrological cycle, especially in regions with varied topography. While E3SM includes a runoff routing component representing water transport in the river network, the lateral transport of water at the subgrid scale within the land model has previously not been taken into account. With the recent development of topographic units within the ELM subgrid data structure, there is an opportunity to simulate hillslope hydrologic connectivity by introducing water transport along topographic gradients. We expect that more realistic representation of hillslope hydrologic processes will lead to improved predictions of both soil water content and river network flows. Lateral transport of water at and near the surface is represented as a sub-grid process in this new code development. Water is tracked as it moves from higher to lower elevations within a gridcell. This capability uses the nested hierarchical sub-grid scheme within ELM to connect water fluxes from sub-grid elements with higher elevation to those with lower elevation. This data record consists of a single document (pdf format) that describes the theoretical basis for the hillslope hydrology processes added to ELM, and describes the modifications made to the ELM code. The Methods section of this metadata record includes a link to the public E3SM code repository where the exact code modifications as integrated in E3SM can be accessed. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

Thornton, Peter E [ORNL] (ORCID:0000000247595158)↗

Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape: Modeling Archive

This modeling archive is in support of the Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) publication "Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape", by Murphy et al. (2025). This archive contains model input files and outputs from landscape-scale simulations conducted using ELM, the land model component of the Department of Energy’s Energy Exascale Earth System Model (E3SM), at the Council NGEE Arctic field site (Council Road mile marker 71) on Alaska’s Seward Peninsula. Input data and model output from two sets of ELM simulations are provided. The first set of simulations were conducted with the two default ELM Arctic plant functional types (PFTs; broadleaf deciduous boreal shrub and a C3 grass) and the second set of simulations were conducted with a set of nine Arctic-specific PFTs including nonvascular mosses and lichens, graminoids, forbs, evergreen dwarf shrubs, three height classes of deciduous shrubs (dwarf, low, and low to tall), and deciduous alder shrubs (Sulman et al., 2021). Parameter names and major parameter changes in the Arctic-specific PFT configuration are described in Sulman et al. (2021) and archived in the Sulman et al. (2021) dataset (see below). Simulations were spatially explicit, covering an approximately 6.4X3.3 km domain at the Council site with a spatial resolution of 100 m for a total of 2,112 simulated grid cells under each ELM PFT configuration. The modeling archive contains meteorological forcing (seven *.nc files and one *.txt file), a domain definition file (one *.nc files), land surface configuration files (two *.nc files), parameter files (two *.nc files), annual ELM output files spanning 1980-2014 (68 *.nc files), and a User’s Guide (*pdf file). Additional information on the provided files is in the “Modeling Archive Contents” section of the User’s Guide. Model outputs are aggregated to the column scale (i.e. PFT-specific outputs are not provided here).

Murphy, Bailey [ORNL] (ORCID:0000000203995221)↗

Improving the Economic Viability of Biological Utilization of Coal Power Plant CO 2 by Improved Algae Productivity and Integration with Wastewater Treatment

The overall goal of this project was to improve the cost-effectiveness of systems using algae to capture and beneficially utilize CO 2 from the flue gas of coal-fired power plants. Algal biomass cultivation is an attractive alternative for carbon capture and utilization because it can uptake more CO 2 per land area than any other photosynthetic crop. Also, the resulting biomass can be used to make valuable large-market commodity products, such as biofuels and animal feed. However, the use of algal carbon capture has been limited by several factors including: (1) high costs for growing algae (>$\$1,300$/ton), (2) large land requirements for algae cultivation, and (3) environmental concerns about the large amount of water and nutrient inputs needed for growing algae. This project has taken direct aim at resolving these key limitations and demonstrated several viable approaches to improve the economic and environmental feasibility of algal carbon capture. In particular, this project demonstrated a significant increase in average annual algal productivity from baseline values of 8 g/m 2 -day to above 20 g/m 2 -day. This supports a much lower projected cost of algae production (<$\$500$/ton) and reduces land requirements by more than 50%. Additionally, this project confirmed the ability to grow multiple algae species with wastewater nutrients, which facilitates the potential for substantial new revenue streams for algae cultivation based on tipping fees for nutrient laden wastewater. This study highlighted that there is more potential value in wastewater nutrient treatment credits than in the primary commodity products made from algae. The use of wastewater inputs also mitigates the concerns associated with the large amount of water needed for growing algae. The algal biomass grown for this project using wastewater and simulated flue gas inputs were characterized for potential use as an animal feed ingredient. The algae had a protein content in the range of 35-40%, which is between some common commodity animal feed products— distiller’s grains (~25-30% protein) and soybean meal (45-50% protein). In-vitro digestion tests using cattle rumen fluids, showed that this algae biomass was best suited for use as “bypass protein”, which is digested in the animal intestine. Based on the protein content and amino acid profile of the algae grown in this study, it was estimated to have market value in the range of $\$190$-$\$280$/ton. There is potential for higher value feed products if the algae content of omega-3 fatty acids or antioxidants is accounted for. This project also did small scale demonstration of forward osmosis algae dewatering and nanofiltration of hydrothermal liquefaction aqueous products, which were shown to improve the cost and energy balance for producing algal products. When all the improvements demonstrated in this study were included in techno-economic analysis, it showed there was a viable pathway to profitable algal CO 2 utilization with a payback period in the range of six to ten years.

01 COAL, LIGNITE, AND PEAT↗

Recommendations to Improve Nuclear Licensing: Update to INL/RPT-23-72206, Recommendations to Improve the Nuclear Regulatory Commission Reactor Licensing and Approval Process

In 2023, various stakeholders had asked for BEA’s thoughts and recommendations to improve the U.S. Nuclear Regulatory Commission’s (NRC) licensing review and approval process. This included an April 14, 2023 request from the House Committee on Energy and Commerce on “information and recommendations to improve the licensing review and approval process, . . . as well as the siting, licensing, construction, and oversight of advanced nuclear reactor technologies.” In response to these requests, BEA prepared and published INL/RPT-23-72206, Recommendations to Improve the Nuclear Regulatory Commission Reactor Licensing and Approval Process (2023 Report). The 2023 Report included 13 recommendations related to streamlining NRC hearings, expediting NRC safety and environmental reviews, otherwise improving NRC licensing, and providing financial benefits to new reactor projects. Many of these earlier recommendations were addressed through various legislative actions or changes made by the NRC. Section 2 of this report addresses the current status of those earlier recommendations. BEA recently received a new request from the House Committee on Energy and Commerce seeking any suggestions for additional areas to examine or potential reforms “that may assist in modernizing the licensing and regulatory process that affects civil nuclear deployment.” Additionally, the new Secretary of Energy has identified initial DOE actions to support unleashing the golden era of American energy dominance, including “Unleash Commercial Nuclear Power in the United States” and “Streamline Permitting and Identify Undue Burdens on American Energy.” Given these developments, BEA has prepared a new set of updated recommendations in this report. The recommendations include updated versions of recommendations from the 2023 Report which have not been fully adopted, as well as entirely new recommendations. This set of recommendations has a slightly broader focus with some recommendations focused on DOE authorizations and some recommendations related to nuclear licensing beyond new reactors. Each recommendation below also identifies whether the recommendation would require legislative action or could be addressed directly by the respective agency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Microstructural basis for improved corrosion resistance of laser surface processed AZ31 Mg alloy

Despite their excellent strength to weight ratio, wider use of Mg alloys for light weighting applications is limited by their poor corrosion resistance, especially in chloride ion-containing environments. The present study shows improved corrosion resistance imparted by laser surface processing (LSP) of a commercial AZ31 (Mg-3Al-1Zn) alloy. Nanosecond laser processing at three different power settings was carried out on the surface of a 1 mm thick rolled AZ31 sheet. Corrosion testing based on ASTM B117 method and several other electrochemical tests indicates substantial enhancement of corrosion resistance in LSP-treated AZ31. The underlying reason behind improved corrosion resistance of LSP-AZ31 surface has been identified using a variety of characterization tools (SEM, TEM, XPS). Formation of a ~0.5 µm thick mixed metal (Mg, Al) oxide surface film together with refinement in the size and number density of Al-Mn intermetallic particles appear to be playing a major role towards improved corrosion resistance after LSP treatment of AZ31 alloy.

Jana, Saumyadeep↗

Robust, High-Performing Maize–Perovskite-Based Solar Cells with Improved Stability

Herein, we focus on improving the long-term chemical and thermomechan-ical stability of perovskite solar cells (PSCs), two major challenges currently limiting their commercial deployment. Our strategy incorporates a long-chain starch polymer into the perovskite precursor. The starch polymer confers multiple beneficial effects by forming hydrogen bonds with the methylammonium iodide precursor, templating perovskite growth that results in a compact and homogeneous film deposited in a simple one-step coating (antisolvent-free). The inclusion of starch in the methylammonium lead iodide films strongly improves their thermomechanical and environmental stability while maintaining a high photovoltaic performance. The fracture energy (G c ) of the film is increased to above 5 J/m 2 by creating a nanocomposite that provides intrinsic reinforcement at grain boundaries. Additionally, improved optoelectronic properties achieved with the starch polymer enable good photostability of the active layer and enhanced resistance to thermal cycling.

14 SOLAR ENERGY↗

Improving the Comprehensive Performance of Na 0.7 MnO 2 for Sodium Ion Batteries by ZrO 2 Atomic Layer Deposition

Sodium ion batteries with Na-Mn-O compounds as cathode have been widely studied as substitutes for lithium ion batteries due to their abundant resources. Still, the relatively poor cycling stability and low capacity of Na-Mn-O compounds significantly limit their applications. Different approaches, including element substitution and surface modification, have been applied to improve the electrochemical performance of those cathode materials. Herein, element doping and coating of ZrO 2 on Na 0.7 MnO 2 particles have been achieved by atomic layer deposition (ALD) followed by post-annealing. The rate capability and cycling stability of the modified material were significantly improved, and the mechanism of performance enhancement was revealed. The ZrO 2 coatings acted as a stable interfacial layer to enhance the cycling stability of Na 0.7 MnO 2 by suppressing side reactions between the electrode and electrolyte. The doping of transition metal ions reduced energy barriers for sodium ion insertion and deintercalation during cycling, further improving the charge and discharge capacity and rate performance of Na 0.7 MnO 2 .

25 ENERGY STORAGE↗

Increasing the Electrolyte Salinity to Improve the Performance of Anion Exchange Membrane Water Electrolyzers

Direct operation of anion exchange membrane water electrolyzers (AEMWEs) with near-neutral pH feeds avoids the use of highly alkaline and corrosive solutions. However, using neutral pH solutions currently faces fundamental operational challenges that diminish performance and reduce long-term stability due to poor solution conductivity and low hydroxide ion concentration. Here, we showed that amending near-neutral pH solutions with low concentrations of alkali metal salts in a dry-cathode configuration substantially improved performance and stability. Adding NaClO 4 (10 mM) to the anolyte reduced the operating voltage by 0.19 to 2.58 V at 500 mA/cm 2 compared to non-saline solutions (2.77 V). However, further increases in the feed salt concentration (100 mM NaClO 4 ) reduced performance (2.64 V) due to a greater co-ion diffusion through the anion exchange membrane. Electrolyzer performance was further improved by utilizing salts with high conductivity such as KNO 3 . Using a saline anolyte reduced ohmic resistance, resulting in smaller applied voltage and energy consumption for hydrogen generation, while the combined effect of the membrane charge and the electric field direction in the dry-cathode feed configuration minimized ion crossover. Thus, increasing the salinity of near-neutral pH solutions represents a cost-effective strategy to improve the performance of AEMWE compared to ultrapure electrolytes, minimizing risks and costs associated with recirculating highly alkaline solutions.

anion exchange membrane water electrolyzer↗

Crosslinked Polyethyleneimine Gel Polymer Interface to Improve Cycling Stability of RFBs

Redox flow batteries are considered a promising technology for grid energy storage. However, capacity decay caused by crossover of active materials is a universal challenge for many flow battery systems, which are based on various chemistries. In this paper, using the vanadium redox flow battery as an example, we demonstrate a new gel polymer interface (GPI) consisting of crosslinked polyethyleneimine with a large amount of amino and carboxylic acid groups introduced between the positive electrode and the membrane. The GPI functions as a key component to prevent vanadium ions from crossing the membrane, thus supporting stable long-term cycling. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) measurements were conducted to investigate the effect of GPI on the electrochemical properties of graphitic carbon electrodes (GCFs) and redox reaction of catholyte. X-ray photoelectron spectroscopy (XPS) and 1 H nuclear magnetic resonance (NMR) spectra demonstrated that the crosslinked GPI is chemically stable for 100 cycles without dissolution of polymers and swelling in the strong acidic electrolytes. Results from inductively coupled plasma mass spectrometry (ICP-MS), Fourier-transform infrared (FTIR) spectroscopy, and energy-dispersive X-ray (EDX) spectroscopy proved that the GPI is effective in maintaining the concentration of vanadium species in their respective half-cells, resulting in improved cycling stability because of it prevents active species from crossing the membrane and stabilizes the oxidation states of active species.

Lim, Hyung-Seok↗

Improved Primary Reference Cell Calibrations for Higher Accuracy Photovoltaic Cell and Module Performance Measurements

The adoption of photovoltaic (PV) modules for clean electricity relies on accurate measurements of their performance, which are essential for estimating their energy production potential. Herein, the calibration chain of PV cells and modules, with particular emphasis on primary reference cell calibrations, is discussed. Also, herein, the direct sunlight method the group has developed for these calibrations is presented and critical improvements and upgrades that lead to calibration uncertainty as low as 0.45% are discussed. The ultimate motivation behind this work is to provide low‐uncertainty performance measurements of PV modules, and lowering the calibration uncertainty of primary reference cells is a key first step toward achieving this goal. As the use of solar electricity continues to grow, the demand for primary reference cell calibrations inevitably increases beyond what the small handful of primary calibration laboratories can provide today. Therefore, this work can serve as a useful guide for implementing primary PV reference cell calibrations using the outdoor method, as well as outlining the critical elements required to make these calibrations highly accurate.

Osterwald, Carl R.↗